Fabricated Return on Investment model to capture less profitable acquisitions considering card member value and total upfront investment Saved INR 48.2M in a year by creating gamer model ROI - cutoffs for incoming applications from 78 channel and product combinations  Impacted 21.3K applications which diminished the gaming rates on credit cards by 25% for both customers and prospects in year 2023 Expansion of compliance approved credit bureau qualifying signals to increase the coverage of gaming models for prospect acquisitions in US Added 8 new rules that led to an impact of 15.1k new applications which saved INR 128.4M of total upfront investment in the year 2023 Increased the model coverage by 27% in a year by creating cutoffs based on average utilization of the cards held by a customer in 5 yearsDesigned vertical strategy approach to accelerate the revenue trajectory to achieve the long term growth target for the US SME market Analyzed internal traction and incremental opportunity in SIC 10 industries by utilizing their Yoy spend growth, acquisitions and attritions Enhanced gamer model to capture customers who have defaulted or have a high spend drop thereby restricting them for welcome offers Rescued INR 2.3M by leveraging spend drops, attrition and defaults in the customers to enhance the offer personalization strategies

Propounded cost reduction opportunities at a plant for a leading Indian multinational mining company with an annual revenue INR 910 B Narrowed the cost worth INR 67.2M for reduction in coke fines generation by defining MECE segments in End to End profitability analysis  Led client meetings to resolve 20+ business critical problems in quality and customer management, reducing operational and legal risks Analyzed the fuel usage in the HEMMs at a plant and diminished the consumption trend (lt/hr) by 9.43% by utilizing the fishbone analysis

Received pre-placement offer for conceiving a product for Risk Management solution for an Oil company with annual revenue INR 98.5B Predicted prices of over 100+ commodities with accuracy > 95 % by building an advanced deep learning model using ensemble approach Garnered profits worth INR 450M annually for commodity trading from the ICE and other exchanges with recommended pricing strategy  Created dashboard with 20+ important indicators & oscillators like the Bollinger Bands, RSI, SMA for the advance technical price analysis

Worked in modelling Indian Insurance Schemes by schemetically studying about various Public Care and Health Insurance Schemes in various developed and developing countries.

Stock Price Prediction•Modelled and predicted the opening values of stock prices of technology giants like Google, listed in the S&P500 index for the year 2019•Successfully implemented the deep learning layer of multivariate LSTM on the daily stock price data of the companies from 2012-2018•Achieved the stock prediction accuracy greater than 99.9% for Google for the year 2019 with a mean squared error of less than 0.19%Predicting the rate of pollution of Beijing•Predicted the rate of pollution of the city for the year 2019 by using per-hour data of pollution, temperature, and pressure from 2014-2018•Implemented the neural networks and the multivariate, Bi-Directional LSTM layer to improve the accuracy for the time-series model•Trained the model with the accuracy greater than 98% using Adam as the optimizer and recieved the mean squared error of just 1.35%